Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the years 2017 - 2021

Updated version v2 (please find the general dataset description below):

We have observed that in version v1 some mowing events were identified at dates that tended to be too early in the season and have thus decided to correct the results using additional phenological observation data from the German Weather Service (DWD, 2026). This 1km x 1km grid contains interpolated dates of the first (in-situ) observed grassland cut in the season. This data is available as an annual time series going back to 1990. We aggregated the data by calculating the average first observed grassland cut per 1km² within the time period 1990 to 2024. The mowing detection results were subsequently corrected by deleting each mowing event that was detected before the average observed first cut minus two standdard deviations. All subsequent mowing events were shifted forward. 

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Grasslands provide a wide range of ecosystem services within agricultural landscapes. Mapping and assessing the status and use intensity of grasslands is thus important for environmental monitoring. We here provide maps with detected mowing events, as a proxy for grassland use intensity, for grassland areas across Germany for the years 2017 to 2021.

The dataset contains maps of grassland mowing activity in Germany, which have been produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire grassland area, i.e. permanent grassland, potentially permanent grassland (e.g. fodder crops) and other extensive areas. They are derived from dense time series of Sentinel-2, Landsat 8 (and 9) data. Map production is based on the methods described in Schwieder et al. (2022). The algorithm used to derive the maps is available as a user-defined function for the FORCE environment (Frantz, D., 2019).

Each annual dataset includes seven layers: (1) the number of detected mowing events, (2) the day of year (DOY) of the first to sixth detected mowing event. Ancillary data layers are available on request. The maps include all areas that have at least once been classified as permanent grassland, cultivated grassland or fallow in the maps of agricultural land use between 2017 and 2021 that are provided by Thünen Institute. The mowing events map therefore contains a substantial overestimation of grassland areas. Please consider to use the respective annual agricultural land use map or any other data source to generate a mask for your purpose.

We provide this dataset "as is" without any warranty regarding the quality or completeness and exclude all liability. Please refer to Schwieder et al. (2022) for the related accuracy assessment and potential limitations and / or contact the authors directly.

The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the provided URL to the datasets (right click on the respective data set --> “copy link address”). By doing so the entire map area or only the regions of interest can be accessed.

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References

DWD Climate Data Center (CDC): Annual grids of several phenological plant stages in Germany, version 0.x, 2026.
https://opendata.dwd.de/climate_environment/CDC/grids_germany/annual/phenology/DGRSS1/ last accessed: 15.07.2026.

Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.

Schwieder, M., Wesemeyer, M., Frantz, D., Pfoch, K., Erasmi, S., Pickert, J., Nendel, C., & Hostert, P. (2022). Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series. Remote Sensing of Environment, 269, 112795.

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Grassland mowing events across Germany © 2022 by Schwieder, Marcel; Lobert, Felix; Tetteh, Gideon Okpoti; Erasmi, Stefan;  licensed under CC BY 4.0. 

Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (MonViA, Monitoring of biodiversity in agricultural landscapes).